Vetted raised a $14 million Series A round in August 2022, led by Insight Partners, with participation from Index Ventures, Bling Capital, and Golden Ventures. This funding followed an earlier seed round in 2020, bringing the company's total funding to approximately $15 million.

Notable investors include Shiva Rajaraman, former VP of Commerce at Meta/Facebook, along with other angel investors. The Series A coincided with the company's rebrand from Lustre to Vetted and its broader market launch.

Vetted is an AI-powered shopping assistant that solves the "analysis paralysis" problem of online shopping. Initially launched as a browser extension called Lustre that overlaid recommendations on Amazon pages, the company rebranded and expanded to a full platform in 2022.

The core product functions as a research layer between consumers and retailers. When a user searches for a product category or asks a specific shopping question (like "What's the best moisturizer for dry skin?"), Vetted's AI analyzes thousands of sources - professional reviews from publications like Wirecutter, user discussions on Reddit, YouTube video reviews, and other expert content.

The system then ranks products based on 10,000+ factors including reviewer credibility, brand reliability, and enthusiast consensus. Users receive a shortlist of top recommendations with clear explanations of why each product made the cut. For instance, a recommendation might note that "this blender appears on multiple experts' 'best of' lists, has positive sentiment on Reddit, and offers strong value for price."

Beyond just recommendations, Vetted automatically compares prices across multiple retailers (Amazon, Walmart, Best Buy, etc.) to find the lowest available price. Users can set price alerts for items they're interested in and see price history charts to determine if now is a good time to buy.

The experience works across multiple touchpoints - website, mobile app, and browser extension. The extension is particularly useful as it activates on any shopping site, providing Vetted's research when viewing products elsewhere and suggesting better alternatives or prices.

Unlike traditional review sites that might update recommendations quarterly or annually, Vetted continuously refreshes its rankings as new reviews emerge or prices change. A team of around 30 in-house product experts oversees the AI's results to verify accuracy, providing a human quality-control layer.

Vetted operates a B2C model that's free for consumers, generating revenue through affiliate commissions when users purchase products through its recommendations. This creates an asset-light business - Vetted carries no inventory and handles no fulfillment, with all transactions ultimately completed on third-party retailer websites.

When a user follows Vetted's recommendation and makes a purchase, the company earns a percentage of the sale value from the retail partner. Commission rates typically range from 1-10% depending on product category and retailer program. With its reported 70% conversion rate (users buying recommended products), the model shows strong potential for sustainable economics.

A key differentiator is Vetted's hybrid approach of AI-driven analysis combined with human oversight. The automated system scales to analyze millions of data points across the web, while the human editorial team ensures quality and accuracy. This balance allows Vetted to cover far more products than manual review sites while maintaining higher reliability than pure algorithms.

The company explicitly does not monetize user data, focusing solely on the affiliate model to maintain alignment with user interests. This positions Vetted as an unbiased alternative to ad-driven shopping experiences like Google and Amazon, where sponsored listings often dominate results.

Operationally, Vetted benefits from a virtuous cycle - as more users engage with the platform and follow its recommendations, the system gathers more data on which suggestions truly satisfy customers, continuously improving its accuracy and strengthening user trust.

Google and Amazon serve as most consumers' default starting points for product research, representing significant competition for user attention. When users Google "best [product]," they typically navigate through multiple sites manually - a habit Vetted aims to replace.

Traditional review publishers like Wirecutter (New York Times), Consumer Reports, CNET, and Gizmodo produce high-quality, editorially-driven recommendations but update less frequently and cover fewer products. Many employ affiliate models similar to Vetted, creating comparable incentive structures.

These established players have brand recognition and trust, but they're limited by the manual nature of their content creation. Vetted leverages their work by incorporating their reviews as inputs to its recommendation engine, positioning itself as a meta-layer rather than a direct competitor.

The AI shopping assistance space is rapidly evolving with several well-funded competitors. PerfectRec takes a different approach by asking users short quizzes about their preferences before making recommendations, relying on human experts for ratings rather than automated content scraping.

Daydream, which raised a $50M seed round, is building an AI-powered shopping search engine initially focusing on fashion, with partnerships across thousands of brands. It emphasizes visual search and personalization - a different angle than Vetted's research-first approach.

Large language model providers are also entering this space. OpenAI has integrated shopping features into ChatGPT, while Perplexity offers product listings with checkout functionality. Amazon's Rufus AI and Shopify's Shop App are building AI recommendations directly into marketplace experiences, creating powerful in-platform alternatives.

Browser extensions like Honey (owned by PayPal) and Capital One Shopping focus primarily on price comparison and coupon application rather than product research. They serve users who have already decided what to buy and just want the best price.

Price comparison engines like Google Shopping aggregate offers across retailers but don't typically help with the initial product selection decision. Vetted incorporates this functionality as part of its broader offering, automatically showing where to get the best price on recommended items.

These tools compete for browser extension real estate and user attention in the purchase journey, though they address different parts of the shopping process than Vetted's core research function.

Vetted's initial wedge was consumer electronics, but its model applies to any retail vertical where consumers research before buying. The company is expanding into home appliances, kitchen gadgets, baby products, outdoor gear, and beauty/skincare.

Each new category taps into new consumer segments and use cases. Someone who might not use Vetted for electronics might use it for researching the best vacuum cleaner or skincare products. The long-tail nature of shopping queries creates nearly unlimited expansion potential across product categories.

More challenging verticals like fashion and apparel, which are driven more by personal taste than specifications, represent significant future opportunities. By incorporating data from style bloggers, YouTube reviews, and consumer sentiment, Vetted could tap into the enormous apparel market.

Currently US-centric in its data sources and retail partnerships, Vetted has substantial room to grow internationally. Adapting the platform for Europe, Asia, and other regions would mean integrating non-English sources, local retailers, and region-specific price comparison.

The global consumer advice market is massive, with shoppers in every country facing similar challenges of information overload and decision fatigue. By localizing effectively, Vetted could become a universally useful tool for online shoppers worldwide.

This horizontal expansion to new categories and countries primarily requires scaling up data ingestion and customization rather than fundamental technology changes, making it a natural growth vector.

Vetted's current focus on affiliate revenue could expand to include premium features. A subscription tier might offer advanced functionalities like longer price history, more frequent alerts, or enhanced personalization for power users.

The company could also move further down the transaction funnel by facilitating checkout or offering a meta-cart feature that allows purchases across multiple retailers. While complex to implement, this would capture more value per transaction.

B2B opportunities represent another expansion path. Vetted's technology and data have value beyond the consumer app - retailers could license the "research summary" capability for their own sites, or brands could purchase aggregate consumer sentiment analysis to improve product development.

Affiliate dependence: Vetted's revenue comes primarily from retail affiliate programs, making it vulnerable to commission rate changes or program terms adjustments. Amazon, for example, has previously cut commission percentages, which would directly impact Vetted's revenue if repeated.

Data access constraints: The platform relies on analyzing content from across the web - including Reddit threads, YouTube videos, and review sites. If major platforms restrict access to their data (as Reddit has recently done with API changes), this could limit Vetted's ability to provide comprehensive recommendations.

AI shopping competition: Large platforms like Google, Amazon, OpenAI, and Perplexity are integrating AI shopping features directly into their products. With enormous existing user bases and deep resources, these competitors could potentially limit Vetted's growth if they can match its recommendation quality while leveraging their distribution advantages.